Model-based Multiple Fault Detection and Isolation for Nonlinear Systems
نویسندگان
چکیده
A model-based detection and isolation (FDI) system based on nonlinear state estimation and high filtering conditions is proposed. A better understanding of the residual trends, calculated from the difference between measurements and the extended Kalman filter (EKF) estimates, can be obtained when a fault occurs by developing a model that is able to predict the behavior of the residuals. This residuals model is utilized as the basis for detection and isolation of multiple faults, having the advantage of distinguishing single and multiple faults from a diverse array of possible faults, a common occurrence in complex processes. The proposed approach is validated using a CSTR, which is simulated using unit operation software CHEMCAD.
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